JP2008165381A - Image processing device and image processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing device and image processing method for processing numerous image processing processes at high speed. <P>SOLUTION: The image processing device 1 for processing a multivalued image 2 has a first processing section 10 for executing calculation with a specific calculating device, and a second processing section 20 for executing calculation with an all-purpose calculation program. The first calculating section 10 is provided with a binarization means 120 for creating a binary image to the multivalued image 2, and a multivalued image processing means 130 for executing calculation on the multivalued image 2. The second processing section 20 is provided with a binary image processing means 220 for executing calculation on the binary image created by the binarization means 120. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to an image processing apparatus and an image processing method.

  In recent years, the digitization of documents using a scanner or the like has progressed. In the digitization, when the volume of the digitized image data is large, there is a problem that inconvenience occurs in handling such as transmission, storage, and display browsing. Specifically, for example, when an A4 size document is read and saved in a full color bitmap format with 300 dpi resolution and 8 bits for each of RGB, the capacity is about 25 Mbytes. Memory and transmission bandwidth are required.

  JPEG compression is known as a technique for reducing the memory and transmission burden by compressing the data size of such a large-capacity file to a small size. However, there is a problem that the image does not have sufficient reproducibility in an image having a steep and complicated density variation as seen in a character portion of a JPEG compressed document. In view of this, there has been a method in which a photographic part and a character part are divided into regions, and compression suitable for each of the photographic part and the character part is performed, and a full-color document is expressed with a small data size while maintaining the quality of the character region. Of these expression methods, a method for realizing expression by PDF (Portable Document Format) (registered trademark) is generally called high-compression PDF (registered trademark).

Japanese Patent Application Laid-Open No. 2004-228561 discloses a technique for recursively performing a process of separating a character part and a picture part and compressing them using JPEG and MMR, respectively. Patent Document 2 discloses a technique of extracting a character region, obtaining coordinates, and displaying the extracted region in a superimposed manner with a base multi-value image. Japanese Patent Application Laid-Open No. 2003-228561 discloses a technique for switching between a character part and a non-character part using mask data in which the non-character part is a white pixel.
Japanese Patent No. 2611012 JP 2006-238405 A JP 2006-197178 A

  However, in Patent Documents 2 and 3, in order to represent a full-color document with a small data size while maintaining the quality of the character area, it is necessary to go through many image processing steps, and there is a problem that processing time is required. .

  The present invention has been invented in order to solve this problem in view of the above points, and an object thereof is to provide an image processing apparatus and an image processing method for processing many image processing steps at high speed. .

  In order to achieve the above object, an image processing apparatus of the present invention is an image processing apparatus that performs predetermined processing on a multi-valued image, and includes a first processing unit that performs arithmetic processing using a dedicated arithmetic processing device. And a second processing unit that performs arithmetic processing using a general-purpose arithmetic processing program, and when the second processing unit can perform the predetermined processing faster than the first processing unit, The second processing unit can be configured to perform the predetermined processing.

  In order to achieve the above object, an image processing apparatus of the present invention is an image processing apparatus that performs processing on a multi-valued image, and includes a first processing unit that performs arithmetic processing using a dedicated arithmetic processing device. And a second processing unit that performs arithmetic processing using a general-purpose arithmetic processing program, and the first processing unit includes binarization means that generates a binary image for the multi-valued image, Multi-value image processing means for performing arithmetic processing on the multi-value image, and the second processing section includes binary image processing means for performing arithmetic processing on the binary image generated by the binarization means. Can be configured.

  In order to achieve the above object, the second processing unit of the present invention creates a composite file for creating a composite file of the calculation result by the multi-value image processing means and the calculation result by the binary image processing means. It can comprise so that a means may be provided.

  In order to achieve the above object, an image processing apparatus according to the present invention includes data transfer means for transferring data between the first processing unit and the second processing unit, and the data transfer The data transferred by the means can be configured to be compressed data and / or binary data.

  In order to achieve the above object, the binary image processing means of the present invention includes an attribute area extraction means for extracting a predetermined attribute area in the binary image, and the attribute area extraction in the binary image. And a mask image generating means for creating a mask image for identifying the attribute area by replacing a pixel in a different area from the attribute area extracted by the means with a white pixel.

  In order to achieve the above object, the multivalued image processing means of the present invention uses the mask image generated by the mask image generating means to generate a foreground image of the multivalued image. And a background image generating means for generating a background image of the multi-value image using the mask image generated by the mask image generating means, and compression encoding the foreground image, the background image and the mask image, respectively. Image compression means.

  In order to achieve the above object, the multi-value image processing means of the present invention uses the mask image generated by the mask image generation means to generate a specific color for generating a specific color image of the multi-value image. An image generating means can be included.

  In order to achieve the above object, the multi-value image processing means of the present invention includes an image reduction means for reducing the image size of an image, and the image reduction means includes the foreground image and the background image. The image compressing means can be configured to compress and encode the foreground image and the background image reduced by the image reducing means.

  In order to achieve the above object, the first processing unit of the present invention includes image expansion means for expanding the multi-valued compressed image transferred from the second processing unit into a multi-valued image. Can be configured.

  In order to achieve the above object, the second processing unit of the present invention includes an image expansion capability determination unit that determines whether the multi-value compressed image can be expanded by the image expansion unit, General-purpose image decompression means for decompressing the value-compressed image, and when the image decompression determination means determines that the multi-value compressed image cannot be decompressed by the image decompression means, the general-purpose image decompression means It can be configured to decompress a value compressed image.

  In order to achieve the above object, the first processing unit of the present invention includes an image enlarging unit that enlarges an image size of an image, and a cutting unit that cuts out an image enlarged by the image enlarging unit. The image enlarging means enlarges the image size of the multi-valued image, the first processing unit performs processing on the enlarged multi-valued image, and the adjusting means performs processing. The multi-value image can be cut out.

  In order to achieve the above object, the first processing unit of the present invention includes image rotation means for rotating an image, and the second processing unit performs image rotation for setting an image rotation amount. An amount setting unit may be provided, and the image rotation unit may be configured to rotate the multi-valued image based on the rotation amount set by the image rotation amount setting unit.

  In order to achieve the above object, the first processing unit of the present invention can be configured to include image correction means for correcting the multi-valued image.

  In order to achieve the above object, the first processing unit of the present invention can be configured to be an ASIC, FPGA, DSP, configurable processor, reconfigurable processor, or MIMD.

  In order to achieve the above object, the image processing method of the present invention includes a first processing unit that performs arithmetic processing using a general-purpose arithmetic processing program, and a second process that performs arithmetic processing using a dedicated arithmetic processing device. An image processing method for performing predetermined processing on a multi-valued image, wherein the first processing unit generates a binary image based on the multi-valued image A multi-valued image processing step in which the first processing unit performs arithmetic processing on the multi-valued image, and a second processing unit performs arithmetic on the binary image generated in the binarizing step. And a binary image processing step for performing processing.

  According to the image processing apparatus and the image processing method of the present invention, many image processing steps can be processed at high speed.

  Hereinafter, the best mode for carrying out the present invention will be described in each embodiment with reference to the drawings. First, the problems to be solved by the image processing apparatus and the image processing method according to the present invention have been described above.

  Currently, a method for speeding up image processing in an image processing apparatus includes hardware such as ASIC (Application Specific Integrated Circuit) and FPGA (Field Programmable Gateway Array), DSP (Digital Signal Constructor), and DSP. There is a method of using a device capable of simple repetitive calculation such as a configurable processor and MIMD (Multiple Instruction / Multiple Data).

  However, for example, an image processing process related to image compression includes complicated image processing with many bit operations, branching, and exception processing, such as a specific attribute part extraction process (character extraction process). Therefore, the method using the above-described device (hardening) is difficult, and as a result, speeding up is difficult.

  In addition, a configuration that allows a device that is good at simple repetitive calculations to perform only the processing can be considered. However, as described above, image data used for digitizing paper originals has a large data capacity, and transmission between devices takes time. As a whole, there was a problem that the speed could not be increased.

  Therefore, in the present invention, a first processing unit that performs arithmetic processing using a dedicated arithmetic processing device and a second processing unit that performs arithmetic processing using a general-purpose arithmetic processing program are prepared. The first processing unit is good at simple repetitive operations such as a product-sum operation, and the second processing unit is excellent in versatility for a complicated operation method such as conditional branching. By performing appropriate processing for each of these processing units (the second processing unit performs image processing that allows the second processing unit to perform processing faster than the first processing unit), For example, image processing such as image compression is performed. As a result, many image processing steps can be processed at a higher speed.

[First Embodiment]
The image processing apparatus according to the first embodiment of the present invention will be described below with reference to FIGS.
(Outline of the device)
First, the configuration of the image processing apparatus according to the first embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating a configuration example of an image processing apparatus according to the first embodiment. In FIG. 1, the image processing apparatus 1 includes a first processing unit 10 that performs arithmetic processing using a dedicated arithmetic processing device and a second processing unit 20 that performs arithmetic processing using a general-purpose arithmetic processing program. The first processing unit 10 includes a high-speed arithmetic device 11, a memory 12, an I / F 13 and the like. The second processing unit 20 is a general-purpose data processing device including an input device 21, a CPU (Central Processing Unit) 22, a memory 23, an HDD (Hard Disk Drive) 24, an I / F 25, an optical drive 26, and the like. (Computer system).

  The high-speed arithmetic device 11 is a device having high arithmetic capability such as product-sum operation. For example, an ASIC, FPGA, DSP, configurable processor, reconfigurable processor, MIMD, or the like. It also has an interface for accessing the memory 12, which is a storage device for storing programs, data, and the like. The I / F 13 is an interface unit for connecting to the outside, here, the second processing unit 20.

  The input device 21 is a device such as a scanner for inputting an image, for example. The CPU 22 is a central processing unit device that performs calculation and processing of data and the like. The memory 23 is a device that stores programs such as RAM (Random Access Memory) and ROM (Read Only Memory), data, and the like. The HDD 24 is a hard disk reading device. The I / F 25 is an interface unit for connecting to the outside, here, the first processing unit 10. The optical drive 26 is a reading device for reading a recording medium 27 such as a CD.

  Although the details will be described later, the first processing unit 10 is excellent in performing simple arithmetic processing (easily circuitized) that performs operations in order of pixels at high speed. The second processing unit 20 is excellent in performing complicated processing such as bit manipulation, branching, and processing with many exceptions at high speed. The transfer rate between the interface units 13 and 25 connecting the first processing unit 10 and the second processing unit 20 is preferably 50 MB / sec or more. For example, a high-speed interface such as PCI Express is used. Use.

  The operation of the image processing apparatus 1 having the above configuration will be briefly described. The HDD 24 or the recording medium 27 of the second processing unit 20 stores a program for realizing the processing functions and processing procedures according to the present invention. If the high-speed computing device 11 of the first processing unit 10 is a device whose program / circuit information can be rewritten from the outside (specifically, FPGA, DSP, configurable processor, reconfigurable processor, MIMD). Such program / circuit information may also be recorded in the HDD 24 or the recording medium 27.

  Here, the document image to be processed by the image processing apparatus 1 is input by the input device 21, for example, and stored in the memory 23, the HDD 24, or the like. The CPU 22 reads a program that realizes the processing functions and processing procedures from the recording medium 27 and the like, and executes image processing based on the program. The result of the image processing is stored in the HDD 24. This result may be stored in a device other than the HDD 24, for example, the memory 23 on the second processing unit 20, a flash memory (not shown) that can be inserted and removed, or a recording medium 27 that is inserted into the optical drive 26. The result of the image processing may be used for mail delivery via a network.

  When the transfer speed between the interface units 13 and 25 connecting the first processing unit 10 and the second processing unit 20 is high enough to sufficiently reduce the time required to transfer image data between the two. For example, a mode in which the first processing unit 10 does not have the memory 12 and the data is placed only in the memory 23 of the second processing unit 20 is also conceivable. Since the image data of a document that is normally handled by an image processing apparatus such as an MFP (Multi Function Peripheral) is large (eg, A4, 25 Mbytes at 300 dpi), it is necessary to spend a cost to connect with an interface that can sufficiently reduce the transfer time. In the first embodiment, a mode in which the first processing unit 10 has the memory 12 will be described.

(Function structure)
Next, the functional configuration of the image processing apparatus according to the first embodiment will be described with reference to FIGS. FIG. 2 is a diagram illustrating an example of a functional block diagram of the image processing apparatus according to the first embodiment. In FIG. 2, the image processing apparatus 1 includes an image expansion unit 110, a binarization unit 120, a multi-value image processing unit 130, a multi-value image acquisition unit 210, a binary image processing unit 220, a summary file creation unit 230, and data transfer. Means 300 is provided. The multi-valued image processing unit 130 includes a foreground generation unit (composite file generation unit) 131, a background generation unit 132, and an image compression unit 133. The binary image processing unit 220 includes a character part extraction unit 221 and a white pixel replacement unit 222.

  The image decompression means 110 decompresses the compressed data to uncompressed data. For example, compressed image data such as JPEG data transferred from a multi-value image acquisition unit 210 described later is expanded into uncompressed image data, and is performed by the high-speed arithmetic device 11 or the like. The binarization unit 120 binarizes the multi-value image data expanded by the image expansion unit 110, for example (binarized data is set as binary image data). Performed by the high-speed arithmetic device 11 or the like. Binarization is a method in which a predetermined threshold is set for the luminance of each pixel of image data, and the pixel value is “0” if it is less than the threshold, and “1” if it is greater than the threshold. The multi-value image processing unit 130 performs arithmetic processing on multi-value image data. The calculation here is, for example, a process for generating a foreground image from multivalued image data which is a process performed by the foreground generating unit 131, a process for generating a background image from multivalued image data which is a process performed by the background generating unit 132, This is compression encoding of multi-valued image data, which is processing performed by the image compression unit 133.

  The multi-value image acquisition unit 210 acquires, for example, a full color document as multi-value image data. For example, the input device 21 or the like performs. The binary image processing unit 220 performs arithmetic processing on binary image data. The calculation here is, for example, extraction of a part having a specific attribute such as a character part from binary image data, which is processing performed by the character part extraction unit (specific attribute region extraction unit) 221, and is performed by the white pixel replacement unit 222. For example, the processing is to replace a portion other than the character portion extracted by the character portion extraction unit 221 in the binary image data, which is processing, with a white pixel. The summary file creation unit 230 creates a composite file by combining a plurality of files by superposition or the like. For example, the calculation result by the multi-value image processing unit 130 and the calculation result by the binary image processing unit 220 are combined, that is, synthesized.

  The data transfer unit 300 transfers data between the first processing unit 10 and the second processing unit 20. For example, the I / Fs 13 and 25 perform this. For example, the multi-value image data input by the multi-value image acquisition unit 210 is transferred to the image expansion unit 110.

  With the configuration of the above function, in the image processing apparatus according to the first embodiment, first, multi-value image data (multi-value image) 2 such as a full-color document acquired by the multi-value image acquisition unit 210 is stored in each block. The data is compressed after being processed. Details of processing in each block will be described in an operation example described later.

  The white pixel replacement unit 222 replaces pixels in a region different from the region of the specific attribute (character portion) extracted by the character extraction unit 221 in the binary image data with the white pixel, thereby replacing the specific attribute (character portion). It can be said that it includes a function as mask image generation means for creating mask image data or the like for identifying the region.

(Operation example)
Next, an operation example of the image processing apparatus according to the first embodiment will be described with reference to FIGS. FIG. 3 is an operation sequence diagram according to an operation example of the image processing apparatus according to the first embodiment. FIG. 4 is an image example for explaining an operation example of the image processing apparatus according to the first embodiment.

  Here, by performing predetermined image processing on a full-color document (multi-valued image) (see FIG. 4A), it is expressed with a small data size while maintaining the quality of the character area (FIG. 4I). The operation to be referred to will be described. In this operation example, description will be made using a general full-color image document including an image portion and a character portion shown in FIG.

  First, the multi-value image obtaining unit 210 obtains a full-color document (see FIG. 4A) as multi-value image data (S101). The data format of the multi-value image data is JPEG data which is compressed data here. In step S102, the data transfer unit 300 transfers the multi-value image data acquired by the multi-value image acquisition unit 210 to the image expansion unit 110 (S102).

  In step S103, the image expansion unit 110 expands the JPEG data transferred in step S102 into uncompressed data (S103). Here, the image decompression means 110 decompresses compressed data such as JPEG data into uncompressed data. FIG. 4B shows an example of an image that has been subjected to image expansion.

Proceeding to step S104, the binarizing means 120 binarizes the multi-valued image data expanded to uncompressed data at step S103 (S104). The binarized data (see FIG. 4C) is set as binary image data. The binarization processing performed here includes a method of using only the G component of the RGB components, a method of calculating the luminance Y from the RGB components, and binarizing. Note that the luminance Y in the latter case is expressed by the following equation.
Y = 0.299R + 0.587G + 0.114B
Here, the method of using only the G component of the RGB components, the luminance Y is calculated from the RGB components, and the formula for obtaining the luminance is composed of a simple product-sum operation. It can be processed. When the binarization method using only the G component is used, black characters are binarized to the same extent as binarization by luminance, but some color characters may be inferior in terms of image quality to binarization by luminance. As for the threshold value, there are a method of changing the threshold value while referring to surrounding pixels and a method of binarizing the entire surface with a single threshold value. It shall be performed with one threshold value.

  In step S105, the data transfer unit 300 transfers the binary image data generated in step S104 to the binary image processing unit 220 of the first processing unit 10 (S105). Here, the binary image data has a data size smaller than that of full color data, and is, for example, 1/24 of the size of RGB full-color data of 8 bits. Therefore, the time required for calculation and transfer can be shortened. Note that the binary image data transferred here may be compressed. In that case, the time required for the transfer can be further reduced. In this case, however, it is desirable to determine whether the time required for compression / expansion or the transfer time is shorter.

  In step S106, the character part extraction unit 221 extracts a portion having a specific attribute, here the position of the character portion, from the binary image data transferred in step S105 (S106). In order to extract the position of the character part from the binary image data in step S106, the method disclosed in Patent Document 1 is used. Other character area extraction techniques that have already been made public may be used.

  In step S107, the white pixel replacement unit 222 erases black pixels other than the character portion in the binary image data in which the position of the character portion is extracted in step S106 (S107). Character mask image data (see FIG. 4D), which is binary image data of only the character portion, is obtained by the processing in steps S106 and S107.

  In step S108, the data transfer unit 300 transfers the character mask image data, which is the binary image data generated in step S107, to the multi-value image processing unit 130. The transferred character mask image data is the first character image data. Is stored in the memory 12 of the processing unit 10 (S108).

  Proceeding to step S109, the foreground generation means 131 generates a foreground image (see FIG. 4E), which is a character layer, based on the multivalued image data expanded in step S103 (S109). Here, the color of the pixel at the position of the pixel constituting the character portion is extracted and used as the character color. The color of the character is determined in units of pixels, a rectangular unit having a predetermined size, and a unit of pixels constituting the character for each connected component. A foreground image is generated based on the determined color.

  Proceeding to step S110, the background generation unit 132 generates a background image (see FIG. 4F) that is an image in which the character portion is deleted based on the multivalued image data expanded in step S103 (S110). Here, an image is generated by replacing the pixels in the character part with the surrounding colors in the multi-valued image data.

  In step S111, the image compression unit 133 compresses the foreground image and the background image generated in steps S109 and S110 by DCT (Discrete Cosine Transform) or the like to generate JPEG compressed image data (S111). In step S108, an MMR compressed image is generated based on the character mask image data transferred from the binary image processing unit 220. 4 (g) and 4 (h) show the compressed foreground image and background image, respectively.

  In step S112, the data transfer unit 300 transfers the foreground image and the background image generated in step S111 to the summary file creation unit 230 (S112). Subsequently, the summary file creation unit 230 superimposes the character mask image (see FIG. 4D) on the foreground image (see FIG. 4G) and the background image (see FIG. 4H), The foreground images remaining in the pixels corresponding to the black pixel portion are combined so as to be displayed in an overlapping manner (see FIG. 4 (i)) (S113). At this time, as shown in FIG. 4 (i), the characters are pasted on the background image and can be seen in the same manner as the original image. The data format (representation means) of the summary file is PDF (registered trademark). The data format of the summary file is not limited to this case.

  Through the processing described above, the image processing apparatus according to the first embodiment performs predetermined image processing on the acquired full-color document (multi-valued image) 2, thereby reducing small data while maintaining the quality of the character area. The operation expressed in size was performed. Here, the predetermined image processing is divided into simple pixel sequential processing such as binarization processing, complicated processing such as specific attribute portion extraction processing (character extraction processing) and summary file generation processing.

  In the first embodiment, the first processing unit 10 is a device suitable for each of the above processes, that is, a device suitable for simple pixel sequential processing such as binarization processing, smoothing processing, and sharpening processing. A second processing unit 20 which is a device suitable for complicated processing such as specific attribute portion extraction processing and summary file generation processing is prepared, and the types of data exchanged between the devices are limited to binarized data and compressed data As a result, the overall processing speed can be increased. Further, when compression is performed by the above method, the file size is effectively reduced.

  Note that the multi-valued image acquired in step S101 of this operation example is JPEG data, but may be other compressed data or non-compressed data. The reason why the multi-value document image acquired in the first embodiment is JPEG data is to reduce the time required for image data transfer, but whether or not to compress it depends on the time required for compression, expansion and transfer, and additional The cost may be determined in view of the entire system using the image processing apparatus 1.

  In step S109 and / or S110 of the first embodiment, the foreground generation unit 131 and the background generation unit 132 are binary image data having only a specific attribute (character portion) obtained by the processing of steps S106 and S107. A character mask image may be used to generate a foreground image and a background image of a multivalued image, respectively.

[Second Embodiment]
Hereinafter, an image processing apparatus according to the second embodiment of the present invention will be described with reference to FIGS. FIG. 5 is a diagram illustrating an example of a functional block diagram of the image processing apparatus according to the second embodiment.

  In the first embodiment described above, by performing predetermined image processing on the acquired full-color document (multi-valued image data) 2, an operation for expressing the character area with a small data size is performed. It was. Here, the acquired full-color document (multi-valued image data) 2 is classified into foreground, background, and selection data (character mask image) by the foreground generation means 131, background generation means 132, character part extraction means 221 and the like. ing. Therefore, a region related to a specific color or lightness (for example, black characters) is included in the foreground, for example, and is not reproduced with a single color or lightness related to the specific color or lightness when reproducing an image. There has been a problem of being reproduced with an aggregate of color or lightness.

  For example, when a device that performs image processing is a printer (or a multifunction device) or the like and an area related to a specific color or brightness is black characters, the printer reproduces and outputs an image (that is, at the time of printing). In other words, the black characters contained in the toner cannot be output by the black toner alone, and may be output by an aggregate of other toners (cyan, magenta, yellow). Therefore, black characters or the like included in the printed image may appear blurred.

  Here, when reproducing an image, an area related to a specific color or lightness (for example, black characters) included in the image can be reproduced with a single color or lightness related to the specific color or lightness (black or lightness zero). An embodiment in which image processing is performed will be described.

  The configuration of the image processing apparatus according to the second embodiment is the same as that according to the first embodiment described above, and a description thereof is omitted here.

(Function structure)
Next, the functional configuration of the image processing apparatus according to the second embodiment will be described with reference to FIG. FIG. 5 is a diagram illustrating an example of a functional block diagram of the image processing apparatus according to the second embodiment. The example of the functional block diagram shown in FIG. 5 is different from the functional block diagram of the first embodiment (see FIG. 3) in that a specific color image generating unit 134 is added. Therefore, the specific color image generation unit 134 will be described here.

  The specific color image generation unit 134 generates a specific color image using, for example, the mask image transferred from the binary image calculation unit 220 in the multi-value image expanded by the image expansion unit 110. A specific color image refers to a color of a pixel at the position of a pixel constituting a specific attribute area such as a character portion in a multi-value image when the color of the pixel is a specific color such as black or red. It is an image generated by using a specific color.

  For example, a black character portion of a general multi-valued image has an irregular distribution (variation) in saturation, brightness, and the like. By the black character portion determination process such as determining that the saturation, brightness, etc. of the color of the pixel at the pixel constituting the black character portion is a value lower than a predetermined threshold value is within the irregular distribution range. If it is determined that the pixel is in an irregular distribution range, a specific color image is generated by processing such as setting the pixel color to black.

  The color of the character part may be determined in units of pixels as described above, but is not limited to this case. It may be determined by a rectangular unit of a predetermined size or by a pixel unit constituting a character for each connected component. When the specific color is black, the black character image that is the specific color image can be a binary image. By expressing the binary image in black of a single color, it can be expressed in black even in printing or the like.

(Operation example)
Next, an operation example of the image processing apparatus according to the second embodiment will be described with reference to FIGS. FIG. 6 is an operation sequence diagram according to an operation example of the image processing apparatus according to the second embodiment. FIG. 7 is an image example for explaining an operation example of the image processing apparatus according to the second embodiment.

  Here, a description will be given focusing on the difference in operation in each step of the operation example of the first embodiment that is added to the specific color image generation unit 134 described above. Note that (a), (b), and (c) in FIG. 7 are the same images as (d), (e), and (f) in FIG. 4, respectively. In the first embodiment described above, the composite file (FIG. 4 (i)) was created based on the images of FIGS. 4 (d), (e), and (f). Here, however, FIG. It differs in that it is created based on the specific color image shown. In addition, since the process which concerns on step S201-S211 is the same as the process which concerns on step S101-S111 in FIG. 3, description is abbreviate | omitted.

  Proceeding to step S212, the specific color image generating unit 134 uses the character mask image data, which is binary image data of only the character part obtained by the processing of steps S206 and S207, and multi-values expanded in step S203. A specific color image of the image data, here, a black character image (FIG. 7D) is generated (S212).

In step S213, the data transfer unit 300 transfers the foreground image and the background image generated in step S211 and the specific color image generated in step S212 to the file creation unit 230 (S213). Subsequently, the summary file creation unit 230 combines the foreground image and the background image by superimposing the character mask image, and further superimposing the black character image (FIG. 7D) (see FIG. 7E). (S213).
By the processing described above, in the image processing apparatus according to the second embodiment, in addition to the first embodiment, when reproducing an image, an area related to a specific color or brightness (for example, black characters) included in the image is Image processing is performed so that reproduction is possible with a single color or lightness (black or zero lightness) relating to the specific color or lightness. That is, the specific color image generation unit 134 of the first processing unit 10 generates an image in which a region related to a specific color or lightness is expressed by a single color or lightness related to the specific color or lightness at high speed. be able to.

[Third Embodiment]
An image processing apparatus according to the third embodiment of the present invention will be described below with reference to FIG. Here, in addition to the first and second embodiments described above, an embodiment in which image processing is performed so as to generate a summary file with a small file size at high speed will be described. The configuration of the image processing apparatus according to the third embodiment is the same as that according to the first embodiment described above, and a description thereof is omitted here.

(Function structure)
Next, the functional configuration of the image processing apparatus according to the third embodiment will be described with reference to FIG. FIG. 8 is a diagram illustrating an example of a functional block diagram of the image processing apparatus according to the third embodiment. The example of the functional block diagram shown in FIG. 8 is different from the functional block diagram of the first embodiment (see FIG. 3) in that an image reducing unit 135 is added. Therefore, here, the difference from the functional block diagram shown in FIG.

  The image reducing unit 135 reduces the image size of the image. For example, the image sizes of the foreground image and the background image generated by the foreground generation unit 131 and the background generation unit 132 are reduced. The image compression unit 133 compresses and encodes the foreground image or the background image whose image size has been reduced by the image reduction unit 135.

  By adding the image reducing means 135 as described above, in the image processing apparatus according to the third embodiment, in addition to the first and second embodiments described above, the foreground image, the background image, and the selection data (character portion). Thus, it is possible to generate a summary file with a small file size while maintaining the quality of the character area. The processing performed by the image reducing unit 135 is processing for reducing the size of the image before reduction by calculation, and includes a nearest neighbor method, a bilinear method, a bicubic method, an area average method, and the like. When the length of one side of the image before reduction is a multiple of the image size after reduction, the calculation can be simplified by using the area averaging method, that is, it can be processed at high speed.

[Fourth Embodiment]
The image processing apparatus according to the fourth embodiment of the present invention will be described below with reference to FIGS. Here, in addition to the above-described first to third embodiments, an embodiment in which image processing is performed at higher speed in consideration of device characteristics of the first processing unit 10 that performs arithmetic processing by the high-speed arithmetic device 11 will be described. . The configuration of the image processing apparatus according to the fourth embodiment is the same as that according to the first embodiment described above, and a description thereof is omitted here.

(Function structure)
Next, the functional configuration of the image processing apparatus according to the fourth embodiment will be described with reference to FIG. FIG. 9 is a diagram illustrating an example of a functional block diagram of the image processing apparatus according to the fourth embodiment. The example of the functional block diagram shown in FIG. 9 is different from the example of the functional block diagram of the first embodiment (see FIG. 3) in that an image clipping unit 136 and an image enlarging unit 140 are added. Therefore, here, the image cutting unit 136 and the image enlarging unit 140 will be described focusing on differences from the functional block diagram shown in FIG.

  The image enlargement unit 140 enlarges the image size of the multi-value image data expanded by the image expansion unit 110. The image cutting unit 136 cuts a predetermined area from the multi-value image data. For example, the area enlarged by the image enlargement unit 140 is cut out.

  The operation performed in the image processing apparatus according to the fourth embodiment by adding the image cutting unit 136 and the image enlarging unit 140 as described above will be described. First, device characteristics of the first processing unit 10 which is a premise of the operation description will be described.

  The high-speed computing device 11 of the first processing unit 10 such as an ASIC, FPGA, DSP, configurable processor, reconfigurable processor, MIMD or the like has a single data access unit of, for example, 64 bytes. It has the characteristic of the boundary of the access unit of data depending on the device (hereinafter referred to as “boundary”). The boundary is restricted by the circuit configuration of the device, the burst length of the internal interface, the image compression format, and the like.

  In the image processing apparatus according to the fourth embodiment, the boundary values of the multivalued image data to be processed are adjusted by the image clipping unit 136 and the image enlarging unit 140 in consideration of the above-described device boundary characteristics. The details of the data boundary adjustment will be described later with a focus on the operations relating to the image cropping unit 136 and the image enlarging unit 140.

(Operation example)
Next, operations performed by the image processing apparatus according to the fourth embodiment will be described with reference to FIG. FIG. 10 is a diagram for explaining the operation of the image processing apparatus according to the fourth embodiment. Here, the operation of performing the above-described data boundary adjustment on the multi-valued image data (see FIG. 10A) expanded by the image expansion unit 110 will be described. The simplified multi-valued image data shown in FIG. 10A has a data size of 8 bytes per pixel, 100 pixels in the horizontal direction (= 800 bytes), and 150 pixels in the vertical direction (= 1200 bytes). And Further, it is assumed that the boundary of the high-speed arithmetic device 11 is 64 bytes.

  First, the image enlarging means 140 enlarges the image size of the multi-value image data. Here, the high-speed computing device 11 can process at high speed when the image size of the multi-valued image data takes a multiple value of 64 bytes. Therefore, the multi-valued image data shown in FIG. 10A is enlarged so that the image size becomes a multiple of 64 bytes. Specifically, the horizontal direction is 104 pixels (= 832 bytes (13 × 64 bytes)), and the vertical direction is 152 pixels (= 1216 bytes (19 × 64 bytes) (see FIG. 10B)). A black pixel is assigned to each pixel in the range of 1. The pixel to be assigned is not limited to a black pixel, and may be a white pixel or a repetition of adjacent pixels. In the case of repetition of adjacent pixels, there is an advantage that the degree of influence is reduced when image processing is performed on multi-valued image data. Various image processes such as the value conversion unit 120, the foreground generation unit 131, and the background generation unit 132 are performed (see FIG. 10C), and then the image cropping unit 136 is enlarged by the image enlargement unit 140. By cutting the area, the image is returned to the original multi-valued image data (see FIG. 10D).

  With the processing described above, in the image processing apparatus according to the fourth embodiment, data boundary adjustment is performed on the multi-value image data (see FIG. 10A) expanded by the image expansion unit 110. For this reason, in addition to the effects of the first to third embodiments, in consideration of characteristics such as device boundary constraints, the processing for expressing a full-color document with a small data size is performed at a higher speed while maintaining the quality of the character area. be able to.

  That is, when the high-speed arithmetic device 11 of the multi-value arithmetic processing unit 10 operates faster when the boundary adjustment is performed, various image processes are processed at high speed by the image enlarging means 140 included in the first processing unit 10. Furthermore, an output result with an appropriate image size can be obtained by the image cutting means 136. As a result, a series of image processing can be speeded up.

  It can be said that the image enlargement unit 140 includes a function as a data boundary adjustment unit that adjusts the boundary of data such as an image based on the boundary of the high-speed arithmetic device 11 having boundary constraints.

[Fifth Embodiment]
An image processing apparatus according to the fifth embodiment of the present invention will be described below with reference to FIG. Here, in addition to the above-described first to fourth embodiments, an embodiment in which the original direction of an image is rotated and image processing is performed on the rotated image at high speed will be described. The configuration of the image processing apparatus according to the fifth embodiment is the same as that according to the above-described first embodiment, and a description thereof will be omitted here.

(Function structure)
Next, the functional configuration of the image processing apparatus according to the fifth embodiment will be described with reference to FIG. FIG. 11 is a diagram illustrating an example of a functional block diagram of the image processing apparatus according to the fifth embodiment. The example of the functional block diagram shown in FIG. 11 is different from the example of the functional block diagram of Embodiment 1 (see FIG. 3) in that an image rotation unit 150 and an image rotation amount setting unit 240 are added. Therefore, here, the image rotation unit 150 and the image rotation amount setting unit 240 will be described focusing on differences from the functional block diagram shown in FIG.

  The image rotation amount setting means 240 sets the image rotation amount. For example, the rotation amount and whether or not the image needs to be rotated are set by user input in an operation unit (not shown) in the image processing apparatus 1 or image data analysis of the image acquired by the multi-valued image acquisition unit 210. The image rotation unit 150 rotates the image according to the image rotation amount set by the image rotation amount setting unit 240.

  With the configuration of the functions described above, the image processing apparatus according to the fifth embodiment rotates the original direction of the image and performs image processing on the rotated image at high speed. As a result, the output result obtained by rotating the original direction of the image can be extracted at high speed. Note that the memory 12 that is a storage unit of the first processing unit 10 can also store information related to the rotation amount of the image transferred from the second processing unit 20.

[Sixth Embodiment]
An image processing apparatus according to the sixth embodiment of the present invention will be described below with reference to FIG. Here, in addition to the first to fifth embodiments described above, an embodiment will be described in which image processing is performed to extract an output result subjected to correction processing such as image quality at high speed. The configuration of the image processing apparatus according to the sixth embodiment is the same as that according to the first embodiment described above, and a description thereof is omitted here.

(Function structure)
Next, the functional configuration of the image processing apparatus according to the sixth embodiment will be described with reference to FIG. FIG. 12 is a diagram illustrating an example of a functional block diagram of the image processing apparatus according to the sixth embodiment. The example of the functional block diagram shown in FIG. 12 is different from the functional block diagram of the first embodiment (see FIG. 3) in that an image correction unit 160 is added. Therefore, here, the image correction unit 160 will be described focusing on the difference from the functional block diagram shown in FIG.

  The image correction unit 160 performs a predetermined correction process on the image. For example, correction processing such as sharpening, smoothing, contrast adjustment, brightness adjustment, and HSV correction is performed on the image expanded by the image expansion unit 110. The sharpening process contributes to improving the readability of the character portion of the image. Smoothing contributes to improving the quality of the binary image generated in the subsequent processing. Contrast adjustment, brightness adjustment, and HSV correction contribute to quality improvement of the entire image and correction reflecting the user's intention. The image correction unit 160 may use any one of these correction units, or may be used a plurality of times, for example, in combination.

  With the configuration of the above function, the image processing apparatus according to the sixth embodiment performs image processing for outputting an output result subjected to correction processing such as image quality at high speed. The image correction unit 160 is included in the first processing unit 10, thereby enabling a reduction in processing time. That is, an output result obtained by improving the image quality or arbitrarily correcting the image quality can be extracted at high speed.

[Seventh Embodiment]
An image processing apparatus according to the seventh embodiment of the present invention will be described below with reference to FIG. Here, in addition to the above-described first to sixth embodiments, even if the multi-valued image 2 is compressed image data that cannot be decompressed by the image decompressing means 110 of the first processing unit 10, a normal series An embodiment for performing the image processing at a high speed will be described. The configuration of the image processing apparatus according to the seventh embodiment is the same as that according to the first embodiment described above, and a description thereof is omitted here.

(Function structure)
Next, the functional configuration of the image processing apparatus according to the seventh embodiment will be described with reference to FIG. FIG. 13 is a diagram illustrating an example of a functional block diagram of the image processing apparatus according to the seventh embodiment. In the example of the functional block diagram shown in FIG. 13, an example of the functional block diagram of the first embodiment is that a compressed data decompression determination unit (image expansion capability determination unit) 250 and a general-purpose image expansion unit 260 are added (FIG. 13). 3). Therefore, here, the compressed data decompression enable determination unit 250 and the general-purpose image decompression unit 260 will be described focusing on the difference from the functional block diagram shown in FIG.

  The compressed data expansion possibility determination unit 250 determines whether the multi-valued compressed image data acquired by the multi-value image acquisition unit 210 can be expanded by the first processing unit 10. The general-purpose image decompressing means 260 decompresses the multi-value compressed image data using a general-purpose arithmetic processing program.

  With the configuration of the above function, in the image processing apparatus according to the seventh embodiment, first, the compressed data decompression determination unit 250 determines that the multi-value compressed image data acquired by the multi-value image acquisition unit 210 is the first processing unit. In step 10, it is determined whether expansion is possible. If it is determined that it is possible, the image expansion means 110 of the first processing unit 10 expands the multi-valued compressed image data as in the first embodiment. If it is determined that it is not possible, the general-purpose image decompressing means 260 decompresses the multi-value compressed image data using a general-purpose arithmetic processing program.

  Therefore, it can be shown below. This is because, in addition to the effects in the first to sixth embodiments, the high-speed arithmetic device 11 of the first processing unit 10 is flexible such as ASIC, FPGA, reconfigurable processor, MIMD other than DSP, configurable processor. It is possible to solve the problem that a device lacking in nature cannot handle various types of compressed data and cannot execute a series of image processing.

  That is, the compressed data decompression determination unit 250 determines whether the multi-valued compressed image data can be decompressed by the first processing unit 10, and if not, the general-purpose image decompression unit of the second processing unit 20. A series of image processing is normally performed even if the compressed image data acquired by the multi-valued image acquisition unit 210 is compressed image data that cannot be expanded by the first processing unit 10 by being expanded by 260 and transferring the data. Can be terminated.

  As described above, the present invention has been described based on each embodiment, but the present invention is not limited to the requirements shown here, such as combinations with other elements listed in the above embodiments. With respect to these points, the present invention can be changed within a range that does not detract from the gist of the present invention, and can be appropriately determined according to the application form.

1 is a diagram illustrating a configuration example of an image processing apparatus according to a first embodiment. It is a figure which shows the example of the functional block diagram of the image processing apparatus which concerns on this Embodiment 1. FIG. FIG. 6 is an operation sequence diagram according to an operation example of the image processing apparatus according to the first embodiment. 3 is an image example for explaining an operation example of the image processing apparatus according to the first embodiment. It is a figure which shows the example of the functional block diagram of the image processing apparatus which concerns on this Embodiment 2. FIG. FIG. 10 is an operation sequence diagram according to an operation example of the image processing apparatus according to the second embodiment. 10 is an image example for explaining an operation example of the image processing apparatus according to the second embodiment. It is a figure which shows the example of the functional block diagram of the image processing apparatus which concerns on this Embodiment 3. FIG. It is a figure which shows the example of the functional block diagram of the image processing apparatus which concerns on this Embodiment 4. FIG. It is a figure for demonstrating operation | movement of the image processing apparatus which concerns on this Embodiment 4. FIG. It is a figure which shows the example of the functional block diagram of the image processing apparatus which concerns on this Embodiment 5. FIG. It is a figure which shows the example of the functional block diagram of the image processing apparatus which concerns on this Embodiment 6. FIG. It is a figure which shows the example of the functional block diagram of the image processing apparatus which concerns on this Embodiment 7. FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Image processing apparatus 10 1st process part 11 High-speed arithmetic device 12 Memory 13 I / F
20 Second processing unit 21 Input device 22 CPU
23 Memory 24 HDD
25 I / F
26 Optical drive 27 Storage medium 110 Image expansion means 120 Binarization means 130 Multi-value image processing section 131 Foreground generation means 132 Background generation means 133 Image compression means 134 Specific color image generation means 135 Image reduction means 136 Image cutout means 140 Image enlargement Means 150 Image rotation means 210 Multi-valued image acquisition means 220 Binary image processing section 230 Summary file creation means 240 Rotation amount setting means 250 Compressed data decompression possibility judgment means 260 General-purpose image decompression means

Claims (15)

An image processing apparatus that performs predetermined processing on a multi-valued image,
A first processing unit that performs arithmetic processing using a dedicated arithmetic processing device;
A second processing unit that performs arithmetic processing using a general-purpose arithmetic processing program;
Have
2. The image processing apparatus according to claim 1, wherein when the second processing unit can perform the predetermined processing faster than the first processing unit, the second processing unit performs the predetermined processing. An image processing apparatus that processes multi-valued images,
A first processing unit that performs arithmetic processing using a dedicated arithmetic processing device;
A second processing unit that performs arithmetic processing using a general-purpose arithmetic processing program;
Have
The first processing unit includes binarization means for generating a binary image for the multi-value image, and multi-value image processing means for performing arithmetic processing on the multi-value image,
The image processing apparatus, wherein the second processing unit includes a binary image processing unit that performs arithmetic processing on the binary image generated by the binarization unit.   The said 2nd process part is provided with the synthetic | combination file creation means which produces the synthetic file of the calculation result by the said multi-value image processing means, and the calculation result by the said binary image processing means. Image processing apparatus. Data transfer means for transferring data between the first processing unit and the second processing unit;
The image processing apparatus according to any one of claims 1 to 3, wherein the data transferred by the data transfer means is compressed data and / or binary data. The binary image processing means includes:
Attribute region extraction means for extracting a predetermined attribute region in the binary image;
In the binary image, a mask image generating means for creating a mask image for identifying the attribute area by replacing a pixel in an area different from the attribute area extracted by the attribute area extraction means with a white pixel;
The image processing apparatus according to claim 2, further comprising: The multi-value image processing means includes
Foreground image generation means for generating a foreground image of the multi-valued image using the mask image generated by the mask image generation means;
Using a mask image generated by the mask image generating means, a background image generating means for generating a background image of the multi-valued image;
Image compression means for compressing and encoding each of the foreground image, the background image, and the mask image;
The image processing apparatus according to claim 5, further comprising:   The multi-value image processing means includes specific color image generation means for generating a specific color image of the multi-value image using the mask image generated by the mask image generation means. 6. The image processing apparatus according to 6. The multi-value image processing means includes image reduction means for reducing the image size of the image,
The image reduction means reduces the image size of the foreground image and the background image, and the image compression means compresses and encodes the foreground image and the background image reduced by the image reduction means. The image processing apparatus according to claim 6 or 7.   The said 1st process part is provided with the image expansion | extension means to expand | deploy the multi-value compression image transferred from the said 2nd process part to a multi-value image. An image processing apparatus according to 1. The second processing unit includes:
Image decompression determination means for determining whether the multi-value compressed image can be expanded by the image expansion means;
General-purpose image decompression means for decompressing the multi-valued compressed image,
10. The general-purpose image decompression unit decompresses the multi-valued compressed image when the image decompression determination unit determines that the multi-value compressed image cannot be decompressed by the image decompression unit. An image processing apparatus according to 1. The first processing unit includes:
Image enlargement means for enlarging the image size of the image;
Cutting means for cutting out the image enlarged by the image enlargement means,
The image enlarging means enlarges an image size of the multi-valued image, the first processing unit performs processing on the enlarged multi-valued image, and the adjusting means performs the process. The image processing apparatus according to claim 2, wherein an image of a multi-valued image is cut out. The first processing unit includes image rotation means for rotating an image,
The second processing unit includes image rotation amount setting means for setting an image rotation amount,
12. The image processing apparatus according to claim 2, wherein the image rotation unit rotates the multi-valued image based on a rotation amount set by the image rotation amount setting unit.   The image processing apparatus according to claim 2, wherein the first processing unit includes an image correction unit that corrects the multi-valued image.   The image processing apparatus according to claim 1, wherein the first processing unit is an ASIC, FPGA, DSP, configurable processor, reconfigurable processor, or MIMD. An image processing apparatus that includes a first processing unit that performs arithmetic processing using a general-purpose arithmetic processing program and a second processing unit that performs arithmetic processing using a dedicated arithmetic processing device, and performs predetermined processing on a multi-valued image An image processing method in
A binarization step in which the first processing unit generates a binary image based on the multi-valued image;
A multi-value calculation step in which the first processing unit performs a calculation process on the multi-value image;
A binary calculation step in which the second processing unit performs calculation processing on the binary image generated in the binarization step;
An image processing method comprising:

Images